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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
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GEOPHIRES Simulations for Deep Direct Use (DDU) Projects

This folder contains the GEOPHIRES codes and input files for running the base case scenarios for the six deep direct-use (DDU) projects. The six DDU projects took place during 2017-2020 and were funded by the U.S. Department of Energy Geothermal Technologies Office. They investiga...
Beckers, K. National Renewable Energy Laboratory
Jun 30, 2020
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
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Wister, CA Downhole and Seismic Data

This submission contains Downhole geophysical logs associated with Wister, CA Wells 12-27 and 85-20. The logs include Spontaneous Potential (SP), HILT Caliper (HCAL), Gamma Ray (GR), Array Induction (AIT), and Neutron Porosity (NPOR) data. Also included are a well log, Injection T...
Akerley, J. Ormat Nevada Inc
Dec 18, 2010
16 Resources
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